Solid state imagers, for example, CCD, CMOS and others, are widely used in imaging applications such as in digital still and video cameras. Many implementations of digital cameras include system-on-a-chip (SOC) imagers, which integrate a sensor core with image processing technology in one monolithic integrated circuit. The sensor core may include the pixel array, row and column logic, analog readout circuitry, and analog-to-digital conversion. The image processing technology may include circuitry for processing digitized sensor core signals using hardware, software or a combination of both.
One important aspect of digital cameras employing solid state imagers is that they be user friendly, particularly for amateur photographers. One method by which digital cameras accomplish this user-friendliness is by providing a wide range of automatic functions (“auto-functions”), such as, for example, auto-focus, auto-exposure and auto-white balance. Camera and/or imager parameters must be set in accordance with current scene conditions for proper operation of the automatic functions. These functions allow an amateur user to take a higher quality image than would be possible without these auto-functions, such as automatic focus, white balance, and exposure control. Some auto-functions, such as, for example, auto-focus may be controlled by the camera itself using inputs from the imager, whereas other auto-functions, such as, for example, auto-exposure and auto-white balance may be controlled by the imager within the camera.
In current cameras, it is challenging to accomplish these automatic tasks quickly. It takes a long time to set the camera and/or imager parameters when the solid state imager is unable to determine the value of important image characteristics (such as the average brightness of the scene) quickly.
Often, for certain automatic functions, the solid state imager must take several sequential images of the scene using different settings while collecting statistics about the scene from these images prior to an actual capture of an image. Scene information is used in statistical analysis to set the camera and/or imager parameters for auto-functions. This usually requires the acquisition of several image frames until the camera and/or image parameters are adjusted to the desired values for an actual image capture. However, this procedure consumes significant amounts of time, especially for large image sizes.
One reason why the imager is unable to determine the necessary values for setting the camera and/or imager parameters in a single image frame is that the dynamic range of the imager pixels is not large enough. The dynamic range for a pixel is commonly defined as the ratio of its largest non-saturating signal to the standard deviation of its noise under dark conditions. The dynamic range is limited on an upper end by the charge saturation level of the pixel photosensor, and on a lower end by noise imposed limitations and/or quantization limits of an analog-to-digital converter used to produce a digital signal from analog pixel signals. The dynamic range of a scene is the contrast ratio between its brightest and darkest parts. An image with a dynamic range higher than that of the pixels in the imager cannot be captured in just a single exposure. Accordingly, several images must be acquired and analyzed with each new exposure setting as part of an auto-exposure process before a proper integration time is set for the imager. When the dynamic range of a pixel is too small to accommodate the variations in light intensities of the imaged scene e.g., by having a low saturation level, luminance clipping and image distortion occurs. For example, when a digital camera is exposed to bright light after working in dark conditions many of the pixels will be oversaturated and the output signal is clipped.
One way to solve this too small dynamic range problem would be to increase the dynamic range of the pixels. However, one downside to increasing the dynamic range of a pixel is that generally it requires a larger pixel. Larger pixel size may not be a feasible option for small size applications.
Another solution that has been proposed to speed up the process of setting camera and/or imager parameters in accordance with current scene conditions is that once image data information is collected for the entire image frame only a subset of the data is used in the statistical analysis portion of the parameter setting process. The drawback to this method, however, is that information on the entire frame must still be acquired, which still may take too much time, and is thus undesirable.
Accordingly, there is a desire and need for a method, apparatus and system for quickly setting camera and/or imager parameters in accordance with current scene conditions to facilitate the use of the auto-functions of a camera system.